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Showing results 1 to 10 of approximately 13.
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Journal Article
The Phillips Curve during the Pandemic: Bringing Regional Data to Bear
The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the country that took relatively large hits to their unemployment rate and employment-population ratio during the pandemic have had lower inflation, on average, than areas that took relatively small hits. And, just as prior to the pandemic, the inverse relationship between inflation and unemployment continues to be statistically stronger for the prices of services than of goods.The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the ...
Report
Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression
We propose a new, computationally-efficient way to approximate the “grouped fixed-effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to the GFE objective; moreover, we recast this objective as a standard Generalized Method of Moments problem. We replicate the empirical results of Bonhomme and Manresa (2015) and show that our estimator delivers almost identical ...
Report
Micro Responses to Macro Shocks
We study estimation and inference in panel data regression models when the regressors of interest are macro shocks, which speaks to a large empirical literature that targets impulse responses via local projections. Our results hold under general dynamics and are uniformly valid over the degree of signal-to-noise of aggregate shocks. We show that the regression scores feature strong cross-sectional dependence and a known autocorrelation structure induced only by leads of the regressor. In general, including lags as controls and then clustering over the cross-section leads to simple, robust ...
Working Paper
Mean Group Distributed Lag Estimation of Impulse Response Functions in Large Panels
This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses of common shocks in large panels with one or two cross-section dimensions. We derive sufficient conditions for asymptotic normality, and document satisfactory small sample performance using Monte Carlo experiments. Three empirical illustrations showcase the usefulness of MGDL estimators: crude oil price pass-through to U.S. city- and product-level retail prices; retail price effects of U.S. monetary policy shocks; and house price effects of U.S. monetary policy shocks.
Journal Article
Where Do the Wealthiest Get Their Wealth?
An analysis using data from Norway identifies the top 0.1% of wealth accumulators and then traces how their wealth evolved from their 20s to their 50s.
Working Paper
Mean Group Distributed Lag Estimation of Impulse Response Functions in Large Panels
This paper develops Mean Group Distributed Lag (MGDL) estimation of impulse responses in large panels with one or two cross-section dimensions. Sufficient conditions for asymptotic consistency and asymptotic normality are derived, and satisfactory small sample performance is documented using Monte Carlo experiments. MGDL estimators are used to estimate the effects of crude oil price increases on U.S. city- and product-level retail prices.
Discussion Paper
The Phillips Curve during the Pandemic: Bringing Regional Data to Bear
The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the country that took relatively large hits to their unemployment rate and employment-population ratio during the pandemic have had lower inflation, on average, than areas that took relatively small hits. And, just as prior to the pandemic, the inverse relationship between inflation and unemployment continues to be statistically stronger for the prices of services than of goods. The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the ...
Working Paper
A Composite Likelihood Approach for Dynamic Structural Models
We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models. We present a number of situations where the methodology has the potential to resolve well-known problems. In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.
Working Paper
Local Projections for Applied Economics
The dynamic causal effect of an intervention on an outcome is of paramount interest to applied macro- and micro-economics research. However, this question has been generally approached differently by the two literatures. In making the transition from traditional time series methods to applied microeconometrics, local projections can serve as a natural bridge. Local projections can translate the familiar language of vector autoregressions (VARs) and impulse responses into the language of potential outcomes and treatment effects. There are gains to be made by both literatures from greater ...
Journal Article
The Phillips Curve during the Pandemic: Bringing Regional Data to Bear
The Phillips curve appears to have held up well at the regional level during the COVID-19 era. Areas of the country that took relatively large hits to their unemployment rate and employment-population ratio during the pandemic have had lower inflation, on average, than areas that took relatively small hits. And, just as prior to the pandemic, the inverse relationship between inflation and unemployment continues to be statistically stronger for the prices of services than of goods.